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Feature extraction from speech signals based on representation learning strategies using pre-trained autoencoders

Home Page: https://jcvasquezc.github.io/AEspeech/

License: MIT License

Python 100.00%

autoencoders deep-learning deep-neural-networks representation-learning speech-analysis speech-processing

aespeech's Introduction

Hi there, I'm Camilo 👋

I have performed research and development activities related to signal processing and machine learning for health-care and biometric applications since five years now, both in academic and industrial partners. Passionate about Machine learning, deep learning, speech processing, and natural language processing technologies. Some technologies I enjoy working and I am familiar with include Pytorch, Transformers, Sklearn, Pandas, FastAPI, Docker, among others.

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Find me around the web 🌎:

Personal web jcvasquezc.github.io
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aespeech's Issues

Training network

Hello, I have reproduced your code. Could you please tell me the new features of the autoencoding generated by your examples.py file? If you want to use KNN and SVM to classify later, should the labels be added in the classification,Do you have the following code for classification? I would like to use it for reference. Thank you

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